🏛️ The Information Retrieval Crypt
cs.IR: Where Information Retrieval papers rest without their code.
11581
Total Papers
9061
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371
Twilight
2149
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18.6%
Survival Rate
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A Study of Factuality, Objectivity and Relevance: Three Desiderata in Large-Scale Information Retrieval?
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Query Expansion via structural motifs in Wikipedia Graph
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A Hybrid Approach to Domain-Specific Entity Linking
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Identifying Actionable Messages on Social Media
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Classifying and Ranking Microblogging Hashtags with News Categories
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Establishing Performance Baselines in Fine-Tuning, Retrieval-Augmented Generation and Soft-Prompting for Non-Specialist LLM Users
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Rethinking E-Commerce Search
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AE-smnsMLC: Multi-Label Classification with Semantic Matching and Negative Label Sampling for Product Attribute Value Extraction
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K-PERM: Personalized Response Generation Using Dynamic Knowledge Retrieval and Persona-Adaptive Queries
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GEAR-Up: Generative AI and External Knowledge-based Retrieval Upgrading Scholarly Article Searches for Systematic Reviews
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Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Exposure
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Attribute Simulation for Item Embedding Enhancement in Multi-interest Recommendation
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Hierarchical Matrix Factorization for Interpretable Collaborative Filtering
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Efficient Neural Ranking using Forward Indexes and Lightweight Encoders
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Collaboration and Transition: Distilling Item Transitions into Multi-Query Self-Attention for Sequential Recommendation
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The Cartographer
Overview of LiLAS 2020 -- Living Labs for Academic Search
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If the Sources Could Talk: Evaluating Large Language Models for Research Assistance in History
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An Efficient Content-based Time Series Retrieval System
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Generative Retrieval with Semantic Tree-Structured Item Identifiers via Contrastive Learning
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Pre-trained Neural Recommenders: A Transferable Zero-Shot Framework for Recommendation Systems
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L^2R: Lifelong Learning for First-stage Retrieval with Backward-Compatible Representations
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Enhancing Transformers without Self-supervised Learning: A Loss Landscape Perspective in Sequential Recommendation
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